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        <title>Incorporating Circumstances into Narrative Event Prediction</title>
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    <name type="personal">
        <namePart type="given">Shichao</namePart>
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    <name type="personal">
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    <name type="personal">
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        <namePart type="family">Yuan</namePart>
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            <namePart type="given">Xuanjing</namePart>
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            <namePart type="given">Lucia</namePart>
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    <abstract>The narrative event prediction aims to predict what happens after a sequence of events, which is essential to modeling sophisticated real-world events. Existing studies focus on mining the inter-events relationships while ignoring how the events happened, which we called circumstances. With our observation, the event circumstances indicate what will happen next. To incorporate event circumstances into the narrative event prediction, we propose the CircEvent, which adopts the two multi-head attention to retrieve circumstances at the local and global levels. We also introduce a regularization of attention weights to leverage the alignment between events and local circumstances. The experimental results demonstrate our CircEvent outperforms existing baselines by 12.2%. The further analysis demonstrates the effectiveness of our multi-head attention modules and regularization.</abstract>
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    <identifier type="doi">10.18653/v1/2021.findings-emnlp.416</identifier>
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%0 Conference Proceedings
%T Incorporating Circumstances into Narrative Event Prediction
%A Wang, Shichao
%A Cai, Xiangrui
%A Wang, HongBin
%A Yuan, Xiaojie
%Y Moens, Marie-Francine
%Y Huang, Xuanjing
%Y Specia, Lucia
%Y Yih, Scott Wen-tau
%S Findings of the Association for Computational Linguistics: EMNLP 2021
%D 2021
%8 November
%I Association for Computational Linguistics
%C Punta Cana, Dominican Republic
%F wang-etal-2021-incorporating-circumstances
%X The narrative event prediction aims to predict what happens after a sequence of events, which is essential to modeling sophisticated real-world events. Existing studies focus on mining the inter-events relationships while ignoring how the events happened, which we called circumstances. With our observation, the event circumstances indicate what will happen next. To incorporate event circumstances into the narrative event prediction, we propose the CircEvent, which adopts the two multi-head attention to retrieve circumstances at the local and global levels. We also introduce a regularization of attention weights to leverage the alignment between events and local circumstances. The experimental results demonstrate our CircEvent outperforms existing baselines by 12.2%. The further analysis demonstrates the effectiveness of our multi-head attention modules and regularization.
%R 10.18653/v1/2021.findings-emnlp.416
%U https://aclanthology.org/2021.findings-emnlp.416
%U https://doi.org/10.18653/v1/2021.findings-emnlp.416
%P 4840-4849

Markdown (Informal)

[Incorporating Circumstances into Narrative Event Prediction](https://aclanthology.org/2021.findings-emnlp.416) (Wang et al., Findings 2021)

• Incorporating Circumstances into Narrative Event Prediction (Wang et al., Findings 2021)

ACL

• Shichao Wang, Xiangrui Cai, HongBin Wang, and Xiaojie Yuan. 2021. Incorporating Circumstances into Narrative Event Prediction. In Findings of the Association for Computational Linguistics: EMNLP 2021, pages 4840–4849, Punta Cana, Dominican Republic. Association for Computational Linguistics.